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Bunyamin Bunyamin^1,2, Taufiq Saidi³, Sugiarto Sugiarto^3,4, Muttaqin Hasan^3,*
Structural Durability & Health Monitoring, Vol.19, No.5, pp. 1089-1109, 2025, DOI:10.32604/sdhm.2025.066887 - 05 September 2025
Abstract Aceh in Indonesia is rich in marine resources and abundant fishery products such as oyster. Traditionally, fishermen only harvest oysters and discard the shells, which can cause pollution and environmental contamination. Waste Oyster Shells (WOS) contain a high percentage of calcium carbonate (CaCO₃) that experiences thermal decomposition at high temperature, following the reaction CaCO₃ → CaO + CO₂ (ΔT = 825°C). At temperature > 900°C, dead-burned lime is formed, which severely influences CaO reactivity. However, the optimum temperature for producing high CaO content is still uncertain. Therefore, this study aimed to determine the optimum calcination temperature to… More >

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Phuong Phan-Vu^*, Thanh Q. Nguyen, Phuoc Trong Nguyen
Structural Durability & Health Monitoring, Vol.19, No.5, pp. 1111-1125, 2025, DOI:10.32604/sdhm.2025.070179 - 05 September 2025
（This article belongs to the Special Issue: Smart Sensors and Smart CFRP Components for Structural Health Monitoring of Aerospace, Energy and Transportation Structures)
Abstract As prestressed concrete (PC) structures age, long-term effects, e.g., creep, shrinkage, and prestress losses, compromise their structural performance. Strengthening these aged PC beams has become a crucial matter. One effective solution is to use externally bonded fiber-reinforced polymer (FRP) sheets; however, limited research has been done on aged PC beams using the FRP, especially for beams with unbonded prestressing strands (UPC beams). Therefore, this research investigates the flexural strengthening efficacy of external FRP sheets on aged UPC beams with unbonded tendons. Aging minimally affected the failure modes of UPC beams, with nonstrengthened beams showing flexural… More >

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Mengqiang Yu¹, Xingcheng Wang¹, Chen Quan¹, Mingxin Sun¹, Yujun Yang², Xiaodong He¹, Wu Sun^2,*, Pengfei Cao^1,*
Structural Durability & Health Monitoring, Vol.19, No.5, pp. 1127-1143, 2025, DOI:10.32604/sdhm.2025.067069 - 05 September 2025
（This article belongs to the Special Issue: Non-contact Sensing in Infrastructure Health Monitoring)
Abstract Accurate measurement of anchor rod length is crucial for ensuring structural safety in tunnel engineering, yet conventional destructive techniques face limitations in efficiency and adaptability to complex underground environments. This study presents a novel wireless instrument based on the standing wave principle to enable remote, non-destructive length assessment. The system employs a master-slave architecture, where a handheld transmitter unit initiates measurements through robust 433 MHz wireless communication, optimized for signal penetration in obstructed spaces. The embedded measurement unit, integrated with anchor rods during installation, utilizes frequency-scanning technology to excite structural resonances. By analyzing standing wave… More >

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Wael A. Altabey^*
Structural Durability & Health Monitoring, Vol.19, No.5, pp. 1145-1165, 2025, DOI:10.32604/sdhm.2025.068922 - 05 September 2025
Abstract In the fabrication and monitoring of parts in composite structures, which are being used more and more in a variety of engineering applications, the prediction and fatigue failure detection in composite materials is a difficult problem. This difficulty arises from several factors, such as the lack of a comprehensive investigation of the fatigue failure phenomena, the lack of a well-defined fatigue damage theory used for fatigue damage prediction, and the inhomogeneity of composites because of their multiple internal borders. This study investigates the fatigue behavior of carbon fiber reinforced with epoxy (CFRE) laminated composite plates… More >

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Guangqing Xiao¹, Xilong Chen¹, Lihai Xu¹, Feilong Kuang², Shaohua He^2,*
Structural Durability & Health Monitoring, Vol.19, No.5, pp. 1167-1181, 2025, DOI:10.32604/sdhm.2025.064450 - 05 September 2025
（This article belongs to the Special Issue: Innovative and Sustainable Materials for Reinforced Concrete Structures)
Abstract This study investigates the flexural performance of ultra-high performance concrete (UHPC) in reinforced concrete T-beams, focusing on the effects of interfacial treatments. Three concrete T-beam specimens were fabricated and tested: a control beam (RC-T), a UHPC-reinforced beam with a chiseled interface (UN-C-50F), and a UHPC-reinforced beam featuring both a chiseled interface and anchored steel rebars (UN-CS-50F). The test results indicated that both chiseling and the incorporation of anchored rebars effectively created a synergistic combination between the concrete T-beam and the UHPC reinforcement layer, with the UN-CS-50F exhibiting the highest flexural resistance. The cracking load and… More >

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Lingfeng Wang¹, Dongbiao Li², Fei Xing^1,3,*, Qiang Wang⁴, Jianjun Shi⁵
Structural Durability & Health Monitoring, Vol.19, No.5, pp. 1183-1201, 2025, DOI:10.32604/sdhm.2025.063701 - 05 September 2025
（This article belongs to the Special Issue: Sensing Data Based Structural Health Monitoring in Engineering)
Abstract With the intelligent upgrading of manufacturing equipment, achieving high-precision and efficient fault diagnosis is essential to enhance equipment stability and increase productivity. Online monitoring and fault diagnosis technology play a critical role in improving the stability of metal additive manufacturing equipment. However, the limited proportion of fault data during operation challenges the accuracy and efficiency of multi-classification models due to excessive redundant data. A multi-sensor and principal component analysis (PCA) and support vector machine (SVM) asymptotic classification (PCSV) for additive manufacturing fault diagnosis method is proposed, and it divides the fault diagnosis into two steps.… More >

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Baojun Qin^1,2, Hong Jiang^1,2,3, Wei Zhang⁴, Xiang Liu^4,*
Structural Durability & Health Monitoring, Vol.19, No.5, pp. 1203-1220, 2025, DOI:10.32604/sdhm.2025.063813 - 05 September 2025
（This article belongs to the Special Issue: Sustainable and Durable Construction Materials)
Abstract The utilization of high-strength steel bars (HSSB) within concrete structures demonstrates significant advantages in material conservation and mechanical performance enhancement. Nevertheless, existing design codes exhibit limitations in addressing the distinct statistical characteristics of HSSB, particularly regarding strength design parameters. For instance, GB50010-2010 fails to specify design strength values for reinforcement exceeding 600 MPa, creating technical barriers for advancing HSSB implementation. This study systematically investigates the reliability of eccentric compression concrete columns reinforced with 600 MPa-grade HSSB through high-order moment method analysis. Material partial factors were calibrated against target reliability indices prescribed by GB50068-2018, incorporating critical More >

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Peng Sun^1,2, Dechen Yao^1,2,*, Jianwei Yang^1,2, Quanyu Long^1,2
Structural Durability & Health Monitoring, Vol.19, No.5, pp. 1221-1239, 2025, DOI:10.32604/sdhm.2025.066098 - 05 September 2025
（This article belongs to the Special Issue: AI-Enhanced Low-Altitude Technology Applications in Structural Integrity Evaluation and Safety Management of Transportation Infrastructure Systems)
Abstract Supervised learning-based rail fastener anomaly detection models are limited by the scarcity of anomaly samples and perform poorly under data imbalance conditions. However, unsupervised anomaly detection methods based on diffusion models reduce the dependence on the number of anomalous samples but suffer from too many iterations and excessive smoothing of reconstructed images. In this work, we have established a rail fastener anomaly detection framework called Diff-Fastener, the diffusion model is introduced into the fastener detection task, half of the normal samples are converted into anomaly samples online in the model training stage, and One-Step denoising… More >

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Xiwei Wang¹, Wanrun Li^1,2,3,*, Wenhai Zhao¹, Yining Wang¹, Yongfeng Du^1,2,3
Structural Durability & Health Monitoring, Vol.19, No.5, pp. 1241-1263, 2025, DOI:10.32604/sdhm.2025.063736 - 05 September 2025
Abstract To address the vibration issues of wind turbine towers, this paper proposes a bidirectional tuned bellow liquid column damper (BTBLCD). The configuration of the proposed BTBLCD is first described in detail, and its energy dissipation mechanism is derived through theoretical analysis. A refined dynamic model of the wind turbine tower equipped with the BTBLCD is then developed. The vibration energy dissipation performance of the BTBLCD in multiple directions is evaluated through two-way fluid-structure coupling numerical simulations. Finally, a 1/10 scaled model of the wind turbine tower is constructed, and the energy dissipation performance of the… More >

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Wenda Ma, Qizhi Tang^*, Huang Lei, Longfei Chang, Chen Wang
Structural Durability & Health Monitoring, Vol.19, No.5, pp. 1265-1286, 2025, DOI:10.32604/sdhm.2025.065294 - 05 September 2025
（This article belongs to the Special Issue: Sensing Data Based Structural Health Monitoring in Engineering)
Abstract Lost acceleration response reconstruction is crucial for assessing structural conditions in structural health monitoring (SHM). However, traditional methods struggle to address the reconstruction of acceleration responses with complex features, resulting in a lower reconstruction accuracy. This paper addresses this challenge by leveraging the advanced feature extraction and learning capabilities of fully convolutional networks (FCN) to achieve precise reconstruction of acceleration responses. In the designed network architecture, the incorporation of skip connections preserves low-level details of the network, greatly facilitating the flow of information and improving training efficiency and accuracy. Dropout techniques are employed to reduce… More >

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Caiping Huang^*, Hui Li, Zihang Yu
Structural Durability & Health Monitoring, Vol.19, No.5, pp. 1287-1304, 2025, DOI:10.32604/sdhm.2025.065930 - 05 September 2025
（This article belongs to the Special Issue: Sensing Data Based Structural Health Monitoring in Engineering)
Abstract Semantic segmentation of concrete bridge defect images frequently encounters challenges due to insufficient precision and the limited computational capabilities of mobile devices, thereby considerably affecting the reliability of bridge defect monitoring and health assessment. To tackle these issues, a concrete defects dataset (including spalling, crack, and exposed steel rebar) was curated and multiple semantic segmentation models were developed. In these models, a deep convolutional network or a lightweight convolutional network were employed as the backbone feature extraction networks, with different loss functions configured and various attention mechanism modules introduced for conducting multi-angle comparative research. The… More >

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679

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Huichao Cao^1,*, Honghe Du¹, Dongnian Jiang¹, Wei Li¹, Lei Du¹, Jianfeng Yang²
Structural Durability & Health Monitoring, Vol.19, No.5, pp. 1305-1325, 2025, DOI:10.32604/sdhm.2025.066002 - 05 September 2025
（This article belongs to the Special Issue: Advanced Detection Technologies and Interpretable Machine Learning Methods in Energy Infrastructure)
Abstract In the production processes of modern industry, accurate assessment of the system’s health state and traceability non-optimal factors are key to ensuring “safe, stable, long-term, full load and optimal” operation of the production process. The benzene-to-ethylene ratio control system is a complex system based on an MPC-PID double-layer architecture. Taking into consideration the interaction between levels, coupling between loops and conditions of incomplete operation data, this paper proposes a health assessment method for the dual-layer control system by comprehensively utilizing deep learning technology. Firstly, according to the results of the pre-assessment of the system layers… More >

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Zhiyong Wan¹, Guozhang Luo², Pailin Fang², Menghui Ji², Zhizhao Ou³, Shaohua He^3,*
Structural Durability & Health Monitoring, Vol.19, No.5, pp. 1327-1341, 2025, DOI:10.32604/sdhm.2025.065177 - 05 September 2025
（This article belongs to the Special Issue: Innovative and Sustainable Materials for Reinforced Concrete Structures)
Abstract This investigation examines the shear performance of concrete T-beams reinforced with thin layers of ultra-high performance concrete (UHPC) through an approach that integrates experimental evaluation, numerical simulation, and practical project verification. The research is based on a real bridge, and in accordance with the similarity principle, three reduced-scale T-beams with varying UHPC thicknesses were fabricated and tested to examine their failure modes and shear behaviors. A finite element model was created to enhance understanding of how UHPC reinforces these structures, while also considering the effects of material strength and arrangement. In addition to the laboratory… More >

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Yuhao Zhang^1,2,3, Peiqiang Zhao^1,2, Xing Chen^1,2, Shaoxuan Zhang⁴, Xinglin Zhang^1,2,*
Structural Durability & Health Monitoring, Vol.19, No.5, pp. 1343-1365, 2025, DOI:10.32604/sdhm.2025.066558 - 05 September 2025
（This article belongs to the Special Issue: Advanced Detection Technologies and Interpretable Machine Learning Methods in Energy Infrastructure)
Abstract The structural integrity monitoring of high-density polyethylene (HDPE) geomembranes in landfill containment systems presents a critical engineering challenge due to the material’s vulnerability to mechanical degradation and the complex vibration propagation characteristics in large-scale installations. This study proposes a dual-stream deep learning framework that synergistically integrates raw vibration signal analysis with physics-guided feature extraction to achieve precise rupture detection and localization. The methodology employs a hierarchical neural architecture comprising two parallel branches: a 1D convolutional network processing raw accelerometer signals to capture multi-scale temporal patterns, and a physics-informed branch extracting material-specific resonance features through continuous More >

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Pinyi Zhao^1,*, Yu Qin², Bo Wu³, Yu Chen¹, Xingyu Chen¹, Jinsheng Wen⁴
Structural Durability & Health Monitoring, Vol.19, No.5, pp. 1367-1386, 2025, DOI:10.32604/sdhm.2025.067558 - 05 September 2025
（This article belongs to the Special Issue: Design, Assessment and Analysis of Steel Structures)
Abstract The impact of longitudinal stiffener configurations on the structural performance of orthotropic steel bridge decks (OSD) was systematically investigated, with emphasis on U-shaped, T-shaped, and rectangular ribs. Finite element analysis was employed to evaluate deformation and stress distribution under three critical loading scenarios: vertical uniform load, vertical eccentric load, and lateral uniform load. Equivalent models ensuring identical steel usage, moment of inertia, and centroid alignment were established to compare five stiffener configurations. Results demonstrate that U-rib configurations exhibit superior performance in controlling local displacements and minimizing stress concentrations. Under eccentric loading, U-ribs significantly reduce deck… More >

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